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Five-CpG-based prognostic signature for predicting survival in hepatocellular carcinoma patients.

Abstract

Objective

Hepatocellular carcinoma (HCC) is a common malignancy associated with high morbidity and mortality rates worldwide. Early diagnosis plays an important role in the improvement of HCC prognosis.

Methods

In this study, we conducted a comprehensive analysis of HCC DNA methylation and gene expression datasets in The Cancer Genome Atlas (TCGA), to identify a prognostic signature for HCC diagnosis and survival prediction. First, we identified differential methylation CpG (dmCpG) sites in HCC samples and compared them with those in adjacent normal liver tissues; this was followed by univariate analysis and Sure Independence Screening (SIS) in the training set. The robustness of the identified prognostic signature was evaluated using the testing set. To explore the biological processes involved in HCC progression, we also performed functional enrichment analysis for overlapping genes between genes containing dmCpG sites (DMGs) and differential expression genes (DEGs) in HCC patients, using data from the Database for Annotation, Visualization, and Integrated Discovery (DAVID).

Results

As a result, we identified five CpG sites that were significantly associated with HCC survival through univariate analysis and SIS. Univariate analysis of clinical characteristics identified age and risk factors (including alcohol consumption and smoking) as independent factors that indicated HCC survival. Multivariate analysis indicated that the integrated prognostic signature (weighted combination of the five CpG sites) that took age and risk factors into consideration resulted in more accurate survival prediction.

Conclusions

This study provides a novel signature for predicting HCC survival, and should be helpful for early HCC diagnosis and personalized treatment.

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  • Authors+Show Affiliations

    ,

    Department of Hepatobiliary Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China.

    ,

    Department of Hepatobiliary Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China.

    Department of Hepatobiliary Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China.

    Source

    Cancer biology & medicine 15:4 2018 Nov pg 425-433

    Pub Type(s)

    Journal Article

    Language

    eng

    PubMed ID

    30766752

    Citation

    Fang, Feng, et al. "Five-CpG-based Prognostic Signature for Predicting Survival in Hepatocellular Carcinoma Patients." Cancer Biology & Medicine, vol. 15, no. 4, 2018, pp. 425-433.
    Fang F, Wang X, Song T. Five-CpG-based prognostic signature for predicting survival in hepatocellular carcinoma patients. Cancer Biol Med. 2018;15(4):425-433.
    Fang, F., Wang, X., & Song, T. (2018). Five-CpG-based prognostic signature for predicting survival in hepatocellular carcinoma patients. Cancer Biology & Medicine, 15(4), pp. 425-433. doi:10.20892/j.issn.2095-3941.2018.0027.
    Fang F, Wang X, Song T. Five-CpG-based Prognostic Signature for Predicting Survival in Hepatocellular Carcinoma Patients. Cancer Biol Med. 2018;15(4):425-433. PubMed PMID: 30766752.
    * Article titles in AMA citation format should be in sentence-case
    TY - JOUR T1 - Five-CpG-based prognostic signature for predicting survival in hepatocellular carcinoma patients. AU - Fang,Feng, AU - Wang,Xiaoqing, AU - Song,Tianqiang, PY - 2019/2/16/entrez PY - 2019/2/16/pubmed PY - 2019/2/16/medline KW - Hepatocellular carcinoma KW - TCGA KW - methylation KW - prognosis KW - prognostic signature SP - 425 EP - 433 JF - Cancer biology & medicine JO - Cancer Biol Med VL - 15 IS - 4 N2 - Objective: Hepatocellular carcinoma (HCC) is a common malignancy associated with high morbidity and mortality rates worldwide. Early diagnosis plays an important role in the improvement of HCC prognosis. Methods: In this study, we conducted a comprehensive analysis of HCC DNA methylation and gene expression datasets in The Cancer Genome Atlas (TCGA), to identify a prognostic signature for HCC diagnosis and survival prediction. First, we identified differential methylation CpG (dmCpG) sites in HCC samples and compared them with those in adjacent normal liver tissues; this was followed by univariate analysis and Sure Independence Screening (SIS) in the training set. The robustness of the identified prognostic signature was evaluated using the testing set. To explore the biological processes involved in HCC progression, we also performed functional enrichment analysis for overlapping genes between genes containing dmCpG sites (DMGs) and differential expression genes (DEGs) in HCC patients, using data from the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Results: As a result, we identified five CpG sites that were significantly associated with HCC survival through univariate analysis and SIS. Univariate analysis of clinical characteristics identified age and risk factors (including alcohol consumption and smoking) as independent factors that indicated HCC survival. Multivariate analysis indicated that the integrated prognostic signature (weighted combination of the five CpG sites) that took age and risk factors into consideration resulted in more accurate survival prediction. Conclusions: This study provides a novel signature for predicting HCC survival, and should be helpful for early HCC diagnosis and personalized treatment. SN - 2095-3941 UR - https://www.unboundmedicine.com/medline/citation/30766752/Five-CpG-based_prognostic_signature_for_predicting_survival_in_hepatocellular_carcinoma_patients L2 - https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/30766752/ DB - PRIME DP - Unbound Medicine ER -